The current approach to business management focuses on increasing the performance of business processes. To achieve the required processes performance means to ensure the required quality and capability of processes. The partial aim of this paper is to confirm the positive effects of the Six Sigma methodology (SSM) on the corporate performance in the Slovak Republic and an investigation of the dependency of SSM implementation on the certified quality management system (QMS) as a set-forward condition via a questionnaire survey carried out in Slovak industrial enterprises. The survey results confirmed the above-mentioned assumptions. The SSM using DMAIC (Define-Measure-Analyze-Improve-Control) was applied in real conditions of two manufacturing enterprises with a different level of quality management system. The results of the research study proved a possibility to implement SSM and to use the same methods in enterprises aside from a level of QMS. However, more remarkable results were achieved by the enterprise which introduced QMS. The first application of SSM in enterprises within specific conditions of furniture production processes can be considered to be a contribution of the research study, as well. The result of the work is the model including the methodology and the appropriate combination of methods and tools for assuring the sustainable performance of the business processes.

Sustainable manufacturing is connected with the effectiveness of production processes. There are several solutions to improve manufacturing sustainability. This paper deals with the possibilities of the utilization of mathematical methods to solve optimization problems in the production process of furniture. The aim of the paper is to create a mathematical model of the key processes in order to maximize productivity and cost reduction by identifying key processes and parameters influencing manufacturing effectiveness. After identification of the parameters describing the key process (milling), an abstract model of the manufacturing process was created. Identified input parameters were the cutting velocity, feed rate, and a total volume of removed material. The output parameters were surface roughness, process duration, and process cost. The experimentally measured and calculated values of the output parameters were analyzed by a multiple regression tool. The method of an artificial neural network was used as a numeric method for optimization. The results showed that the maximal effectiveness of the sub-process can be achieved if the CNC machine is set at the cutting velocity of 4398.23 m·min⁻¹ and feed rate of 11.00 m·min⁻¹. Maximal values of the created neural network showed optimal values of input and output parameters.

This paper focuses on the optimization of a critical operation in the furniture manufacturing process, identifying it as a key priority for improvement by applying Systems Theory. The primary objective of this study is to develop a mathematical model for optimizing the detected key process by employing artificial neural networks (ANNs) which mirror adaptive management principles. Three input and three output parameters significantly impacting the effectiveness of this key process have been systematically identified and experimentally measured. It was necessary to perform multi-objective optimization (MOO), which consisted in achieving the minimum values of cost and process time and the maximum value of the quality index through the optimal setting of the input parameters (cutting speed, feed rate, and volume of removed material). The application of ANNs in MOO in this research study is a novelty in this field. The results obtained through application of the ANN method reveal the optimal values of the examined parameters, which represent the best combination of input technical variables leading to the best results in output economic parameters. This multi-objective optimizing solution facilitates enhanced process efficiency. By integrating Systems Theory, Complexity Theory, and adaptive management, this research advances sustainable process improvements by minimizing resource use, reducing waste, and enhancing overall system efficiency.

Digitalization, including the implementation of artificial intelligence (AI) applications, is one of the key enablers of business agility in contemporary enterprises. Micro and small enterprises (MSEs) are increasingly expected to adopt scalable and cost-effective AI tools as part of their digital transformation. This study investigates the implementation of an AI-powered chatbot in a Slovak micro-enterprise operating an e-commerce platform, aiming to assess its effectiveness in automating customer service processes. Using a mixed-method case study approach, the research combines quantitative data on service performance (e.g., number of inquiries handled, response time, and automation rate) with qualitative insights from employee and customer feedback. The findings show that the chatbot significantly reduced staff workload and improved response speed and customer satisfaction. However, challenges were identified in handling ambiguous queries and maintaining empathetic communication in complex situations, underscoring the need for regular updates and human oversight. The study contributes to the limited empirical literature on AI integration in micro-enterprises and provides practical recommendations for MSEs seeking to enhance their operational efficiency through AI-driven tools without large-scale investments. These results offer a nuanced perspective on how even resource-constrained businesses can benefit from AI adoption when implementation is carefully aligned with their specific needs and capabilities.

The current competitive environment is only favourable to those companies that can cope with changes and use them to their advantage. The innovation of business processes is required to improve financial performance. Scientific works have not yet offered an effective solution to the monitoring of the impact made by process reengineering on corporate financial results. This work presents the case of a business process reengineering in a particular company to improve its performance. The results of implemented reengineering are analysed from the point of view of the impact made on the financial situation of the company. The paper aims to demonstrate the implementation of reengineering and evaluate its impact on the financial standing of a company and its performance. The practical application of reengineering was made according to Hammer and Champy methodology, which is based on the analysis of production processes in the company, the implementation of selected reengineered production processes and the evaluation of the reengineering impact on the corporate financial situation and performance. During the evaluation, the selected indicators of financial performance, activity indicators, the indebtedness indicator, business performance indicators as a cash flow to measure financial flows and the economic value-added (indicator EVA) were calculated and analysed. Subsequent to financial analyses and based on the selected indicators, the authors concluded that the implemented reengineering of the production process increased the performance and value of the company, which had a positive impact on the company’s financial situation. The funds spent on the proper implementation of the reengineering steps were effectively used, and the reengineering process was also timed. This contribution to the body of theoretic knowledge links the implementation of reengineering and the part of the financial analysis, which is related to the preparation, implementation and reengineering results.

Foreign trade belongs among the main sources of economic growth as classical theories of international trade affirm. The aim of the paper is to evaluate the impact of trade balance flows on sectors generating different value-added in the wood-based industries (WBI) of the Czech and Slovak Republics. The multivariate regression method (MLR) was applied to identify the relationship between foreign trade and economic indicators and also specific indicators assessing impacts of foreign trade on the economy of wood-based industries. The results showed that the performance of high value-added production is only slightly affected by foreign trade. It means that both monitored countries do not utilize raw wood so intensively that the positive effects of foreign trade are manifested. Growth in net exports represents a positive influence on the economy of the sector regardless of the value-added rate only if the increase in imports is smaller than in exports. The contribution of the study to existing knowledge is in using specific indicators evaluating trade impacts on the industry’s economy. The article provides new empirical insights into the influence of foreign trade balance flows on the economy of wood-based sectors with a different value-added rate.